Identification of variables associated with the graph structure and applications in neuroscience

• Grant number: 15/21162-4
• Support Opportunities: Scholarships in Brazil - Doctorate
• Start date: April 01, 2016
• End date: August 31, 2019
• Field of knowledge: Physical Sciences and Mathematics - Computer Science - Computing Methodologies and Techniques
• Principal Investigator: André Fujita
• Grantee: Suzana de Siqueira Santos
• Host Institution: Instituto de Matemática e Estatística (IME). Universidade de São Paulo (USP). São Paulo , SP, Brazil
• Associated scholarship(s): 17/12074-0 - Asymptotic behavior of parameter estimators and test statistics for graphs, BE.EP.DR

Abstract

The corpus callosum is the largest white matter structure of the human brain. One of its functions is to facilitate the interaction between the left and right hemispheres. Abnormalities in the corpus callosum morphology have been reported in several neuropsychiatric disorders, such as schizophrenia, autism, attention deficit hyperactivity disorder, alien hand syndrome, personality disorders, and bipolar affective disorder. However the corpus callosum function and its contribution to cognition and behavior is still a topic of debate. Then, finding associations between the corpus callosum morphology and the brain functional connectivity is fundamental for the study of several neuropsychiatric disorders and the corpus callosum function. In this project we propose to attack that problem by measuring the statistical dependence between the structure of the graph representing the brain functional network and corpus callusum morphological features, such as its volume. Then, we will apply the proposed method in data obtained from subjects with autism, which is a complex disorder whose symptoms highly overlap with the agenesis of the corpus callosum (congenital condition resulting in partial or total absence of that structure). One of the main challenges will be to deal with the presence of many sources of variability in the brain functional connectivity. Approaches to attack that problem are essential to integrate graph theory and statistics and can contribute to the study real systems modeled by graphs. (AU)

Scientific publications

(References retrieved automatically from Web of Science and SciELO through information on FAPESP grants and their corresponding numbers as mentioned in the publications by the authors)

SANTOS, SUZANA DE SIQUEIRA; FUJITA, ANDRE; MATIAS, CATHERINE. Spectral density of random graphs: convergence properties and application in model fitting. JOURNAL OF COMPLEX NETWORKS, v. 9, n. 6, p. 27-pg., 2021-10-20. (18/21934-5, 19/22845-9, 17/12074-0, 20/08343-8, 15/21162-4)

FUJITA, ANDRE; LIRA, EDUARDO SILVA; SANTOS, SUZANA DE SIQUEIRA; BANDO, SILVIA YUMI; SOARES, GABRIELA ELEUTERIO; TAKAHASHI, DANIEL YASUMASA. A semi-parametric statistical test to compare complex networks. JOURNAL OF COMPLEX NETWORKS, v. 8, n. 2, APR 2020. (18/17996-5, 18/21934-5, 15/21162-4, 15/01587-0)

JARDIM, VINICIUS CARVALHO; SANTOS, SUZANA DE SIQUEIRA; FUJITA, ANDRE; BUCKERIDGE, MARCOS SILVEIRA. BioNetStat: A Tool for Biological Networks Differential Analysis. FRONTIERS IN GENETICS, v. 10, JUN 21 2019. (14/50884-5, 18/21934-5, 16/13422-9, 15/21162-4, 08/57908-6)

Academic Publications

(References retrieved automatically from State of São Paulo Research Institutions)

SANTOS, Suzana de Siqueira. Consistent parmeter estimators for random graph models and study of the relation between the default-mode network and the corpus callosum volume. 2020. Doctoral Thesis - Universidade de São Paulo (USP). Instituto de Matemática e Estatística (IME/SBI) São Paulo.